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About

About

I hold a Master degree in Bioengineering with specialization in Biomedical Engineering from Faculty of Engineering of the University of Porto, Portugal. I landed a thesis proposal where I had to develop an autonomous robotic system with the ability to reproduce repetitive tasks in a lab environment. During the degree, the passion for applied robotics emerged, so I decided to pursue it in order to integrate and further improve the knowledge in areas such as mechanics, electronics, computer science and biomedics. I joined the CRIIS group which belongs to INESC TEC, in September 2016 as a R&D engineer with responsibilities in developing new robotic solutions to handle industrial problems. My main activities include system mechanical modelation, electronics and software development.

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Details

Details

  • Name

    Cláudia Daniela Rocha
  • Role

    Researcher
  • Since

    01st February 2016
024
Publications

2024

Inspection of Part Placement Within Containers Using Point Cloud Overlap Analysis for an Automotive Production Line

Authors
Costa, M; Dias, J; Nascimento, R; Rocha, C; Veiga, G; Sousa, A; Thomas, U; Rocha, L;

Publication
Lecture Notes in Mechanical Engineering

Abstract
Reliable operation of production lines without unscheduled disruptions is of paramount importance for ensuring the proper operation of automated working cells involving robotic systems. This article addresses the issue of preventing disruptions to an automotive production line that can arise from incorrect placement of aluminum car parts by a human operator in a feeding container with 4 indexing pins for each part. The detection of the misplaced parts is critical for avoiding collisions between the containers and a high pressure washing machine and also to avoid collisions between the parts and a robotic arm that is feeding parts to a air leakage inspection machine. The proposed inspection system relies on a 3D sensor for scanning the parts inside a container and then estimates the 6 DoF pose of the container followed by an analysis of the overlap percentage between each part reference point cloud and the 3D sensor data. When the overlap percentage is below a given threshold, the part is considered as misplaced and the operator is alerted to fix the part placement in the container. The deployment of the inspection system on an automotive production line for 22 weeks has shown promising results by avoiding 18 hours of disruptions, since it detected 407 containers having misplaced parts in 4524 inspections, from which 12 were false negatives, while no false positives were reported, which allowed the elimination of disruptions to the production line at the cost of manual reinspection of 0.27% of false negative containers by the operator. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2024

A Robotic Framework for the Robot@Factory 4.0 Competition

Authors
Sousa, B; Rocha, D; Martins, G; Pedro Costa, J; Padrão, JT; Sarmento, JM; Carvalho, JP; Lopes, S; Costa, G; Moreira, AP;

Publication
2024 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2024

Abstract
Robotic competitions stand as platforms to propel the forefront of robotics research while nurturing STEM education, serving as hubs of both applied research and scientific innovation. In Portugal, the Portuguese Robotics Open (FNR) is an event with several robotic competitions, including the Robot@Factory 4.0 competition. This competition presents an example of deploying autonomous robots on a factory shop floor. Although the literature has works proposing frameworks for the original version of the Robot@Factory competition, none of them proposes a system framework for the Robot@Factory 4.0 version that presents the hardware, firmware, and software to complete the competition and achieve autonomous navigation. This paper proposes a complete robotic framework for the Robot@Factory 4.0 competition that is modular and open-access, enabling future participants to use and improve it in future editions. This work is the culmination of all the knowledge acquired by winning the 2022 and 2023 editions of the competition. © 2024 IEEE.

2023

Quality Control of Casting Aluminum Parts: A Comparison of Deep Learning Models for Filings Detection

Authors
Nascimento, R; Ferreira, T; Rocha, C; Filipe, V; Silva, MF; Veiga, G; Rocha, L;

Publication
2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Abstract
Quality control inspection systems are crucial and a key factor in maintaining and ensuring the integrity of any product. The quality inspection task is a repetitive task, when performed by operators only, it can be slow and susceptible to failures due to the lack of attention and fatigue. This work focuses on the inspection of parts made of high-pressure diecast aluminum for components of the automotive industry. In the present case study, last year, 18240 parts needed to be reinspected, requiring approximately 96 hours, a time that could be spent on other tasks. This article performs a comparison of four deep learning models: Faster R-CNN, RetinaNet, YOLOv7, and YOLOv7-tiny, to find out which one is more suited to perform the quality inspection task of detecting metal filings on casting aluminum parts. As for this use-case the prototype must be highly intolerant to False Negatives, that is, the part being defective and passing undetected, Faster R-CNN was considered the bestperforming model based on a Recall value of 96.00%.

2023

Knee positioning systems for X-ray environment: a literature review

Authors
Lopes, C; Vilaca, A; Rocha, C; Mendes, J;

Publication
PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE

Abstract
The knee is one of the most stressed joints of the human body, being susceptible to ligament injuries and degenerative diseases. Due to the rising incidence of knee pathologies, the number of knee X-rays acquired is also increasing. Such X-rays are obtained for the diagnosis of knee injuries, the evaluation of the knee before and after surgery, and the monitoring of the knee joint's stability. These types of diagnosis and monitoring of the knee usually involve radiography under physical stress. This widely used medical tool provides a more objective analysis of the measurement of the knee laxity than a physical examination does, involving knee stress tests, such as valgus, varus, and Lachman. Despite being an improvement to physical examination regarding the physician's bias, stress radiography is still performed manually in a lot of healthcare facilities. To avoid exposing the physician to radiation and to decrease the number of X-ray images rejected due to inadequate positioning of the patient or the presence of artefacts, positioning systems for stress radiography of the knee have been developed. This review analyses knee positioning systems for X-ray environment, concluding that they have improved the objectivity and reproducibility during stress radiographs, but have failed to either be radiolucent or versatile with a simple ergonomic set-up.

2022

A kinesthetic teaching approach for automating micropipetting repetitive tasks

Authors
Rocha, C; Dias, J; Moreira, AP; Veiga, G; Costa, P;

Publication
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Abstract
Nowadays, a laboratory operator in the areas of chemistry, biology or medicine spends considerable time performing micropipetting procedures, a common, monotonous and repetitive task which compromises the ergonomics of individuals, namely related to wrist musculoskeletal disorders. In this work, the design of a kinesthetic teaching approach for automating the micropipetting technique is presented, allowing to redirect the operator to other non-repetitive tasks, aiming to reduce the exposure to ergonomic risks. The proposed robotic solution has an innovative gripping system capable of supporting, actuating and regulating the volume of a manual micropipette. The system is able to configure the position of diverse laboratory materials, such as lab containers and plates, on the workbench through a collaborative robotic arm, providing flexibility to adapt to different procedures. A projected human-machine interface, which combines the display of information on the workbench with an infrared based interaction device was developed, providing a more intuitive interaction between the operator and the system during the configuration and operation phases. In contrast to the majority of the existing liquid handling systems, the proposed system allows the operator to place the materials freely on the workbench and the usage of different materials' variants, facilitating the implementation of the system in any laboratory. The attained performance and ease of use of the system were very encouraging since all the defined tasks in the conducted experiments were successfully performed by users with minimum training, highlighting its potential inclusion in the laboratory routine panorama.